惠普实验室的社交计算(social-computing)主管伯纳德·胡伯曼(Bernardo Huberman)在最近的一份报告中得出结论：Twitter用户的影响力取决于其tweet传播的深度与广度，而非关注者(follower)的数量。
ABSTRACT
The ever-increasing amount of information owing throughSocial Media forces the members of these networks to com-pete for attention and inuence by relying on other peopleto spread their message. A large study of information propa-gation within Twitter reveals that the majority of users actas passive information consumers and do not forward thecontent to the network. Therefore, in order for individuals to become inuential they must not only obtain attention and thus be popular, but also overcome user passivity. Wepropose an algorithm that determines the inuence and pas-sivity of users based on their information forwarding activ-ity. An evaluation performed with a 2.5 million user datasetshows that our inuence measure is a good predictor of URL clicks, outperforming several other measures that do not explicitly take user assivity into account. We also explicitly demonstrate that high popularity does not necessarily imply high in uence and vice-versa.